Creating Animated Bar Charts
But what are video bar charts in the first place ?
Animated bar charts race which helps one visualize the change in trends over time, these type of charts are very popular on social media as they provide a holistic data story/insight in a concise and easy to understand chart.
A lot of visualization tools like Tableau & Power BI enable you to do so but you can make them quite easily in R as well.
Whaaat?
This document does it using the International Football Match dataset, ranking the top ten countries in terms of international matches played till 2020.
Data pre-processing
The data needs to be pre-processed in a certain format before we move to the visualization bit
df <- read.csv("C:/Users/aishwarya.sharma/OneDrive - insidemedia.net/Dell Lattitude - 5300/Aishwarya/Kaggle/International FIFA Results/results.csv",stringsAsFactors = F)
df$date <- format(as.Date(df$date,, format = "%Y-%m-%d"),"%Y")
home.result <- df %>%
group_by(home_team,date)%>%
summarise(Matches_Played = n())
colnames(home.result)[1] <- "Team"
away.result <- df %>%
group_by(away_team,date)%>%
summarise(Matches_Played = n())
colnames(away.result)[1] <- "Team"
total <- rbind.data.frame(home.result,away.result)
total <- total %>%
group_by(Team,date)%>%
summarise(Total_Matches = sum(Matches_Played))
colnames(total) <- c("Team","Year","Total_Played")
total <- total %>%
group_by(Team)%>%
mutate(Cum_Matches =cumsum(Total_Played))
temp <- total %>%
group_by(Year) %>%
mutate(rank = rank(-Cum_Matches, ties.method = "random"),
Total_Matches_rel = Cum_Matches/Cum_Matches[rank==1],
Total_Played_lbl = paste0(" ",round(Cum_Matches))) %>%
group_by(Team) %>%
filter(rank <=10) %>%
ungroup()
head(temp)## # A tibble: 6 x 7
## Team Year Total_Played Cum_Matches rank Total_Matches_r~ Total_Played_lbl
## <chr> <chr> <int> <int> <int> <dbl> <chr>
## 1 Argent~ 1902 1 1 8 0.0128 " 1"
## 2 Argent~ 1903 1 2 8 0.0247 " 2"
## 3 Argent~ 1905 1 3 10 0.0345 " 3"
## 4 Argent~ 1906 2 5 7 0.0556 " 5"
## 5 Argent~ 1908 3 8 10 0.0816 " 8"
## 6 Argent~ 1909 3 11 10 0.106 " 11"Building a Static Plot
Now we’ll build individual plots for each year. There are a few key aspects with the theme() function that will be altered to make it go well with the animation, like – Only Vertical Grid Lines are drawn and Legends, Axes Title and few more components would be removed from the plot.
staticplot = ggplot(temp, aes(rank, group = Team,
fill = as.factor(Team), color = as.factor(Team))) +
geom_tile(aes(y = Cum_Matches/2,
height = Cum_Matches,
width = 0.9), alpha = 0.8, color = NA) +
geom_text(aes(y = 0, label = paste(Team, " ")), vjust = 0.2, hjust = 1) +
geom_text(aes(y= Cum_Matches,label = Total_Played_lbl, hjust=0)) +
coord_flip(clip = "off", expand = FALSE) +
scale_y_continuous(labels = scales::comma) +
scale_x_reverse() +
guides(color = FALSE, fill = FALSE) +
theme(axis.line=element_blank(),
axis.text.x=element_blank(),
axis.text.y=element_blank(),
axis.ticks=element_blank(),
axis.title.x=element_blank(),
axis.title.y=element_blank(),
legend.position="none",
panel.background=element_blank(),
panel.border=element_blank(),
panel.grid.major=element_blank(),
panel.grid.minor=element_blank(),
panel.grid.major.x = element_line( size=.1, color="grey" ),
panel.grid.minor.x = element_line( size=.1, color="grey" ),
plot.title=element_text(size=25, hjust=0.5, face="bold", colour="grey", vjust=-1),
plot.subtitle=element_text(size=18, hjust=0.5, face="italic", color="grey"),
plot.caption =element_text(size=8, hjust=0.5, face="italic", color="grey"),
plot.background=element_blank(),
plot.margin = margin(2,2, 2, 4, "cm"))Animation
The key function here is transition_states() which stitches the individual static plots together by year. view_follow() is used to give a view as if the background lines (gridlines) are moving as the animation is progressing
anim = staticplot + transition_states(Year, transition_length = 4, state_length = 1) +
view_follow(fixed_x = TRUE) +
labs(title = 'Football Matches Through the Years : {closest_state}',
subtitle = "Top 10 Countries",
caption = "Top 10 Countries with Most Played Football Matches")
# The FPS has to be adjusted as per the data
animate(anim, 1000, fps = 10, width = 1200, height = 1000,
renderer = gifski_renderer("gganim.gif"))